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Download runtime/minatar_synth/games/cate_p.py from neilkale/WeightProgramBench: direct link, hf CLI and curl.
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https://huggingface.co/datasets/neilkale/WeightProgramBench/resolve/main/runtime/minatar_synth/games/cate_p.py
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hf download hf://datasets/neilkale/WeightProgramBench/runtime/minatar_synth/games/cate_p.py
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curl -L -o cate_p.py https://huggingface.co/datasets/neilkale/WeightProgramBench/resolve/main/runtime/minatar_synth/games/cate_p.py
4.8 kB
| from dataclasses import dataclass | |
| import numpy as np | |
| HORIZON = 400 | |
| FRAMES_PER_STEP = 4 | |
| DIRECTIONS = ((1, 0), (0.7, 0.7), (0, 1), (-0.7, 0.7), | |
| (-1, 0), (-0.7, -0.7), (0, -1), (0.7, -0.7)) | |
| class Mover: | |
| x: float | |
| y: float | |
| direction: int | |
| def move(self, speed: float) -> None: | |
| dx, dy = DIRECTIONS[self.direction] | |
| self.x += speed * dx | |
| self.y += speed * dy | |
| def inside(self, low: float, high: float) -> bool: | |
| return low <= self.x <= high and low <= self.y <= high | |
| def clamp(self) -> None: | |
| self.x = min(90, max(9, self.x)) | |
| self.y = min(90, max(9, self.y)) | |
| def touches(self, other: "Mover") -> bool: | |
| return abs(self.x - other.x) < 5 and abs(self.y - other.y) < 5 | |
| class Cate(Mover): | |
| entering: bool = True | |
| class CatePEnvironment: | |
| score_cap = 100 | |
| def __init__(self, sticky_action_prob: float = 0.1, horizon: int = HORIZON): | |
| self.sticky_action_prob = sticky_action_prob | |
| self.horizon = min(horizon, HORIZON) | |
| self.seed(0) | |
| self.reset() | |
| def seed(self, seed: int) -> None: | |
| self.random = np.random.default_rng(seed) | |
| def reset(self) -> None: | |
| self.steps = self.wave_count = self.wave_timer = 0 | |
| self.multiplier = 1 | |
| self.pressed = self.terminal = False | |
| self.player = Mover(50, 50, 0) | |
| self.shot: Mover | None = None | |
| self.entrance: Mover | None = None | |
| self.newest: Cate | None = None | |
| self.cates: list[Cate] = [] | |
| def normalize_score(cls, score: float) -> float: | |
| return min(max(score, 0), cls.score_cap) / cls.score_cap | |
| def act(self, action: int) -> tuple[float, bool]: | |
| if self.terminal: | |
| return 0.0, True | |
| pressed = self.pressed if self.random.random() < self.sticky_action_prob else action == 5 | |
| tap = pressed and not self.pressed | |
| self.pressed = pressed | |
| self.steps += 1 | |
| reward = 0 | |
| for frame in range(FRAMES_PER_STEP): | |
| reward += self._advance_frame(tap and frame == 0) | |
| if self.terminal: | |
| break | |
| self.terminal |= self.steps >= self.horizon | |
| return float(reward), self.terminal | |
| def _advance_frame(self, tap: bool) -> int: | |
| player = self.player | |
| if tap or not player.inside(9, 90): | |
| if tap and self.shot is None: | |
| self.shot = Mover(player.x, player.y, player.direction) | |
| self.multiplier = 1 | |
| player.clamp() | |
| player.direction = (player.direction + 2) % 8 | |
| player.move(0.2) | |
| if self.shot is not None: | |
| if self.shot.inside(9, 91): | |
| self.shot.move(1.5) | |
| else: | |
| self.shot = None | |
| self._spawn() | |
| survivors = [] | |
| reward = 0 | |
| for cate in self.cates: | |
| cate.move(0.2) | |
| if cate.entering: | |
| cate.entering = not cate.inside(9, 90) | |
| elif not cate.inside(9, 90): | |
| corner = not 9 <= cate.x <= 90 and not 9 <= cate.y <= 90 | |
| cate.direction = (cate.direction + (4 if corner else 3)) % 8 | |
| cate.clamp() | |
| if self.shot is not None and cate.touches(self.shot): | |
| reward += self.multiplier | |
| self.multiplier += 1 | |
| if self.newest is cate: | |
| self.newest = None | |
| else: | |
| self.terminal |= cate.touches(player) | |
| survivors.append(cate) | |
| self.cates = survivors | |
| return reward | |
| def _spawn(self) -> None: | |
| if self.wave_timer <= 0: | |
| direction = int(self.random.integers(4)) * 2 | |
| offset = self.random.uniform(9, 90) | |
| x, y = ((-3, offset), (offset, -3), (103, offset), (offset, 103))[direction // 2] | |
| self.entrance = Mover(x, y, direction) | |
| self.wave_count = int(self.random.integers(5, 9)) | |
| self.wave_timer = int(self.random.integers(60, 91)) | |
| if self.wave_count == 0: | |
| self.wave_timer -= 1 | |
| if self.newest is not None and self.newest.inside(3, 97): | |
| self.newest = None | |
| if self.wave_count and self.newest is None and self.entrance is not None: | |
| self.newest = Cate(self.entrance.x, self.entrance.y, self.entrance.direction) | |
| self.cates.append(self.newest) | |
| self.wave_count -= 1 | |
| def state(self) -> np.ndarray: | |
| state = np.zeros((10, 10, 6), dtype=bool) | |
| for channel, movers in ((0, [self.player]), (1, self.cates), (2, [self.shot])): | |
| for mover in movers: | |
| if mover is not None and mover.inside(0, 99.999): | |
| row, col = int(mover.y) // 10, int(mover.x) // 10 | |
| state[row, col, channel] = True | |
| if isinstance(mover, Cate): | |
| state[row, col, 3] |= mover.entering | |
| state[(0, 9), :, 4] = True | |
| state[:, (0, 9), 4] = True | |
| for row, value in enumerate((self.steps, self.player.direction, self.multiplier, | |
| self.shot.direction if self.shot is not None else 0)): | |
| for bit in range(9): | |
| state[row, bit, 5] = bool(value & (1 << bit)) | |
| state[9, 0, 5] = self.pressed | |
| return state | |